Putting a Price on Social Connections

Why weak ties aren’t always strong. “Researchers at IBM and MIT have found that certain e-mail connections and patterns at work correlate with higher revenue production … they used mathematical formulas to analyze the e-mail traffic, address books, and buddy lists of 2,600 IBM consultants over the course of a year. … They compared the communication patterns with performance, as measured by billable hours. They found that consultants with weak ties to a number of managers produced $98 per month less than average. Why? Those employees may move more slowly as they process “conflicting demands from different managers,” the study’s authors write. They suffer from “too many cooks in the kitchen.”

How to introduce people (matchmaking). They also analyzed methods to introduce employees to colleagues they haven’t yet met (to incent people to participate). … “Geyer and his team are digging for signs of shared interests and behaviors among their colleagues. …In their matchmaking efforts, the IBM team tried a variety of approaches. One used a tool favored by Facebook, recommending friends of common friends. Others analyzed the subjects and themes of employees’ postings on Beehive, words they use, and patents they’ve filed. As expected, some of the systems lined up workers with colleagues they already knew. Others were better at unearthing unknowns. But fewer of them turned out to be good matches. To the frustration of the researchers, some of the workers noted that recommendations looked good, yet they didn’t bother contacting the people. “They put them aside for future reference,” Geyer says. “

“To the frustration of the researchers, some of the workers noted that recommendations looked good, yet they didn’t bother contacting the people.”

I can understand that; I’d feel awkward contacting a stranger on the basis of a computer’s recommendation. Perhaps it would be better to ask a third party – such as their nearest common ancestor in the organisational hierarchy – to introduce them, without necessarily mentioning why.

That’s a very interesting point, Mike. I and Neal are working on something similar and one of the ideas is that one matches people who share interests (regardless of whether they have common friends). Alas, that mostly results in recommending strangers… I don’t know how to combine both content-matching and familiar-matching… Any idea?